Monolithic 3D Integration of Analog RRAM‐Based Computing‐in‐Memory and Sensor for Energy‐Efficient Near‐Sensor Computing (Adv. Mater. 22/2024)

Near‐Sensor Computing In article number 2302658, Jianshi Tang and co‐workers demonstrate a prototype M3D‐SAIL chip for energy‐efficient near‐sensor computing by monolithic three‐dimensional integration of an IGZO‐FET based photosensor array, an analog RRAM‐based computing‐in‐memory array, and Si CMO...

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Bibliographic Details
Published in:Advanced materials (Weinheim) 2024-05, Vol.36 (22), p.n/a
Main Authors: Du, Yiwei, Tang, Jianshi, Li, Yijun, Xi, Yue, Li, Yuankun, Li, Jiaming, Huang, Heyi, Qin, Qi, Zhang, Qingtian, Gao, Bin, Deng, Ning, Qian, He, Wu, Huaqiang
Format: Article
Language:English
Subjects:
Analog circuits
Arrays
Computation
computing‐in‐memory
Energy consumption
Indium gallium zinc oxide
InGaZnOx field‐effect transistor
Logic circuits
monolithic 3D integration
near‐sensor computing
resistive random‐access memory
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Summary:Near‐Sensor Computing In article number 2302658, Jianshi Tang and co‐workers demonstrate a prototype M3D‐SAIL chip for energy‐efficient near‐sensor computing by monolithic three‐dimensional integration of an IGZO‐FET based photosensor array, an analog RRAM‐based computing‐in‐memory array, and Si CMOS logic circuits. A video keyframe‐extraction task is implemented, achieving a high classification accuracy of 96.7% and 31.5× lower energy consumption and 1.91× faster computing speed compared to its 2D counterpart.
ISSN:0935-9648
1521-4095
DOI:10.1002/adma.202470164